1. Field of Invention
The present invention relates generally to the field of image analysis. More specifically, the present invention is related to the automatic analysis of cardiac M-Mode views.
2. Discussion of Related Art
In recent years echocardiography has become the most commonly used tool in diagnosis of heart disease. A standard 2D mode shows a planar slice of the heart across a scanning sector. By capturing multiple 2D frames in a video, the heart motion and function can be observed. Its ability to provide continuous view of both structure and motion, to take measurements and to verify functionality using blood and tissue Doppler are ever expanding and becoming more accurate. Yet, the outcome of these tests greatly depends on the sonographer skills, in particular depending on the accurate manual positioning of the sensor and of manually positioned calipers, rulers and markers over the captured images. Ultrasound images are, in general, low quality images. Because of the ultrasound imaging limitations, they have low resolution and suffer from very fuzzy edges, high noise and shadows. Their interpretation requires special training and rich experience, as defined in the “ACC/AHA Clinical Competence Statement on Echocardiography”, 2002. For example, the minimum recommended training for a cardiologist is 6 months, performing at least 150 tests and interpreting another 300 tests.
Many of the required measurements are taken in M-mode—a spatio-temporal representation of the tissue motion along one scanning line of the ultrasound device through the heart. These measurements include estimations of ventricle volume, ejection fraction, tissue thickness, wall motion, valve timing and more. A typical echocardiogram test includes several 2D and M-Mode captures of different viewpoints, according to the “ACC/AHA/ASE 2003 Guideline Update for the Clinical Application of Echocardiography” and takes about 15-20 minutes.
The direct way of capturing and using an M-Mode of the heart is illustrated in FIG. 1 and FIG. 2. First, a 2D mode (see FIG. 1) is used to locate the chamber, reposition the sensor to see a cross section through the chamber and position a cursor (pointed to with an arrow) to pass through the chamber in a direction perpendicular to the walls. Then the scan mode and display mode are switched to M-Mode (FIG. 2). In this mode, the vertical axis corresponds to the z-axis, or depth from the sensor along the cursor line in the 2D mode. The horizontal axis corresponds to time. In this example, roughly two heart cycles are shown. The sonographer records several heart cycles, then freezes the view. The sonographer then places calipers (two vertical dotted lines 202, 204) and takes note of the measurements (from table 206). In this example the sonographer places two calipers, one at the end of diastolic period and the second at the end of systolic period. These calipers measure the short-axis diameter of the left chamber. The caliper-based measurements are then displayed in table 206. This whole process takes place during the patient echocardiogram test.
Hence, Direct M-Mode images can only be taken along a radial cursor line, origin from the sensor focal point. The sonographer has to accurately position the sensor device in a heart-depending orientation, often in conflict with the optimal positioning of the sensor to capture a good cross-section 2D view while avoiding bones, reducing interference and undesired reflections.
Panoramic M-Mode (also known as Anatomic M-Mode) is a process in which one or more synthetic M-Mode images is created from a sequence of 2D (or 3D) mode images by sampling those images along desired line(s) of scan and stacking those as columns in new M-Mode images. Compared to direct M-Mode, Panoramic M-Mode has the advantage of being generated in any direction and location on a 2D image rather than restricted by the sensor location. Panoramic M-Mode, however, suffers from lower temporal resolution, or scanning frequency. Panoramic M-Mode has been found very useful for diagnosis of Ischemia (see e.g., the paper to Lee et al. entitled, “Using Synthetic M-mode Imaging to Measure Temporal Differences in Left Ventricular Contraction Patterns during Ischemia”), measuring LV wall motion, wall thickening and more. Recently, Philips™ introduced Anatomic M-Mode into its EnVisor™ ultrasound system: “ . . . and Anatomical M-mode that makes it easier to keep the M-mode line perpendicular to the anatomy—even in abnormally shaped or positioned hearts—and allows accurate measurements of chambers, walls, and ejection fraction.”
While M-Mode has existed for decades and Panoramic M-Mode has just made its start into medical devices, there has been very little work on automatic analysis of M-Mode images using computer vision techniques. Griffiths et al., in their paper entitled, “Computer assisted M-mode echocardiogram analysis,” use computer display and a tablet to allow users place calipers and mark traces, take measurements and render graphs corresponding to the user's marks on the image. Griffiths et al., however, do not apply any computer vision techniques. Maplica et al., in their paper entitled, “A snake model for anatomic M-mode tracking in echocardiography, Image and Signal Processing and Analysis”, use snakes to track the evolution of a single Doppler blob in a panoramic M-Mode. However, Maplica et al. only deal with Doppler images containing single color blob of interest, while regular M-Mode images show many tissue layers and are more complex to analyze.
In U.S. Pat. No. 5,515,856, Olstad et al. provide a method for the generation of anatomic M-Mode images from 2D echocardiogram sequences. These images can then be used by a physician to aid in diagnosis. Olstad et al., however, do not provide means to automatically analyze the M-Mode image.
Potter et al., in U.S. Patent Publication 2006/0034538 A1, provide a general framework to: display echocardiogram images, take various measurements such as caliper-based measurements, and allow the physician to select measurement results and compose a report. Potter et al. disclose user interface workflow, such as acquiring a mouse click and responding to it, but it does not provide any method for analyzing the images and automatically extracting any measurements.
In U.S. Pat. No. 6,514,207, Ebadollahi et al. provide a method and system for analyzing the complete video of an echocardiogram test, segmenting and recognizing different modes and views along the exam, analyzing the overlay ECG graph, and detecting R-wave, thus segmenting the video into individual heart cycles. Ebadollahi et al., however, only analyze 2D views and do not deal with M-Mode images.
In U.S. Pat. No. 6,708,055, Gelser provides a method for analyzing a single frame of epical four chambers view using standard image processing techniques. Gelser, however, does not deal with M-Mode images. A single 2D view captures only a single snapshot of the heart, does not contain any temporal information and therefore does not allow the computation of an ejection fraction, or any motion-dependent or time-dependent measures.
In U.S. Pat. No. 4,936,311, Oe teaches how to analyze ventricular function using the center-line method, in which the long axis of the chamber in a 2D view is manually marked, followed by the manually marking of the area of difference between systolic and diastolic chamber views. The chamber volume and ejection fraction can then be estimated from the marked lines and regions. The process described by Oe is a labor intensive process. Also, Oe does not provide any image processing or other automatic way to analyze echocardiograms.
Prior art exists on image improvement of echocardiograms, such as reducing speckle as per the teachings of U.S. Pat. No. 6,755,787, wherein these methods may be applied as preprocessing to enhance image quality before applying the algorithm disclosed by Applicant's invention. However none of these prior art techniques teaches how to analyze the image content. Also, none of the existing works consider echocardiogram M-Mode images for automatic indexing and finding similar cases. Further, none of them provides any means to compare two M-Mode images. Hence there is need to define an appropriate representation, a method to efficiently construct it, allow to automatically extract medically meaningful measurements and a similarity measure, which enable the indexing and search for similar cases and therefore assist in multimodal medical decision support. Whatever the precise merits, features, and advantages of the above cited references, none of them achieves or fulfills the purposes of the present invention.